Peajes

plot

plot_dellepiane <- plot_ly(
  data = data, 
  x = ~Fecha, 
  y = ~Dellepiane, 
  type = 'scatter', 
  mode = 'lines+markers',
  name = 'Dellepiane',
  line = list(color = 'darkorange', shape = 'spline', width = 3),  # Smooth line with more prominent color
  marker = list(
    size = 10, 
    color = 'rgba(255, 140, 0, 0.5)',  # Light orange with transparency
    line = list(width = 2, color = 'white')  # Enhanced marker with a white border
  )
) %>%
  layout(
    title = list(
      text = "Trafico Dellepiane a lo largo del tiempo 2014 a 2024",  # Title text
      font = list(size = 20, color = 'darkorange', family = 'Arial'),  # Font adjustments
      xanchor = 'center', 
      yanchor = 'top',
      pad = list(b = 20)  # Padding below title
    ),
    xaxis = list(
      title = "Fecha",
      titlefont = list(size = 14, color = 'black', family = 'Arial', weight = 'bold'),  # Bold title
      tickfont = list(size = 14, color = 'darkorange', weight = 'bold'),  # Bold tick labels
      showgrid = TRUE,  # Show gridlines
      gridcolor = 'lightgrey',
      gridwidth = 0.5
    ),
    yaxis = list(
      title = "Cantidad de vehiculos mensuales",
      titlefont = list(size = 14, color = 'black', family = 'Arial', weight = 'bold'),  # Bold title
      tickfont = list(size = 14, color = 'darkorange', weight = 'bold'),  # Bold tick labels
      showgrid = TRUE,  # Show gridlines
      gridcolor = 'lightgrey',
      gridwidth = 0.5
    ),
    plot_bgcolor = 'whitesmoke',  # Light background color
    paper_bgcolor = 'white',  # White border around the plot
    hovermode = "closest",  # Keep hovermode
    margin = list(t = 80, b = 60, l = 60, r = 60),  # Adjust plot margins
    showlegend = TRUE  # Display the legend
  )

plot_dellepiane

# Filter the data to only include records up to October 2024 for Dellepiane column
data_filtered_dellepiane <- data %>%
  filter(!(year(Fecha) == 2024 & month(Fecha) > 10))  # Exclude data after October 2024

# Aggregate data by year and month for Dellepiane
data_aggregated_dellepiane <- data_filtered_dellepiane %>%
  mutate(anio = year(Fecha), mes = month(Fecha)) %>%  # Extract year and month
  group_by(anio, mes) %>%
  summarise(Mensual_Vehiculos = sum(Dellepiane, na.rm = TRUE)) %>%  # Sum per month for Dellepiane
  group_by(anio) %>%
  summarise(Media_Mensual = mean(Mensual_Vehiculos, na.rm = TRUE))  # Calculate monthly average by year for Dellepiane

## `summarise()` has grouped output by 'anio'. You can override using the
## `.groups` argument.

# Show the table with Spanish labels
data_aggregated_dellepiane

## # A tibble: 11 × 2
##     anio Media_Mensual
##    <dbl>         <dbl>
##  1  2014      2625355.
##  2  2015      2559830.
##  3  2016      2604142.
##  4  2017      2557721.
##  5  2018      2481034.
##  6  2019      2437806.
##  7  2020      1770814.
##  8  2021      2237676.
##  9  2022      2560460.
## 10  2023      2632786.
## 11  2024      2615440.

# Line Chart for Dellepiane average using plotly
line_chart_dellepiane <- plot_ly(data_aggregated_dellepiane, x = ~anio, y = ~Media_Mensual, type = 'scatter', mode = 'lines+markers',
                                 line = list(color = 'darkorange', width = 3),
                                 marker = list(size = 10, color = 'rgba(255, 140, 0, 0.5)', line = list(width = 2, color = 'white'))) %>%
  layout(
    title = "Promedio Mensual de Vehiculos en Dellepiane por Anio",
    xaxis = list(title = "anio", titlefont = list(size = 14, weight = 'bold'), tickfont = list(size = 12)),
    yaxis = list(title = "Media Mensual de Vehiculos", titlefont = list(size = 14, weight = 'bold'), tickfont = list(size = 12)),
    plot_bgcolor = 'whitesmoke',
    paper_bgcolor = 'white',
    margin = list(t = 50, b = 50, l = 50, r = 50)
  )

line_chart_dellepiane